Hi, This is an emergency and I need tonight. I run a moderation in regression an

Question

Hi,

This is an emergency and I need tonight.

I run a moderation in regression and I need an interpretation of my SPSS output.

Please, see the output below and help me with. As you can see, my research question are:

1.Is there an association between gender, socio economic status and math achievement after controlling for minority?

2. Does the effect of socio-economic on math achievement vary across gender?

Thanks

n MATRIX procedure: PROCESS Procedure for SPSS Release 2.16.3 Written by Andrew F Hayes Ph.D www. afhayes .com Documentation available in Hayes (2013 www.guilford.com/p/hayes Model mathach female Statistical Controls CONTROL minority sample size 7185 Outcome mathach Model Summary dfl df2 R-sq MSE 4142 1715 39.2169 414.5451 4.0000 7180.0000 0000 Model coeff LLCI ULCI se 13.5351 0890 152.1062 0000 13.3606 13.7095 constant 2.6818 27.7904 2.4927 0965 0000 2.8710 2.3783 l 0856 female 493 9.2316 0000 1.6710 2622 1844 1.4218 0993 6238 int 1 1551 minority 2.8402 1739 16.3311 0000 3.1811 2.4993 Product terms key: int 1. female R square increase due to interaction (s) R2-chng dfl df2 int 1 0002 2.0214 1.0000 7180.0000 1551 Conditional effect of X on Y at values of the moderator (s) Effect LLCI ULCI 7794 1.5827 2133 7.4190 0000 2.0008 1.1645 0000 1.3783 1493 9.2316 0000 1.6710 1.0856 7794 1.1739 2010 5.8407 0000 1.5679 7799 Values for quantitative moderators are the mean and plus/min us one SD from mean Values for dichotomous moderators are the two values of the moderator JOHNSON-NEYMAN TECHNIQUE Moderator value (8) defining Johnson-Neyman significance region (s) below Value above 2.1506 99.9861 0139 Conditional effect of X on Y at values of the moderator (M) Effect ULCI LICI 8e 3.7581 3.2937 3.7706 2.3638 0010 9569 3.4356 2.2792 6596 3.4554 000% 3.5722 9862 3.1131 2.1946 601B 3.6467 0003 3.3743 1.0149 3.1772 2.7906 2.1101 5444 3.8761 0001 1.0429 2.4681 2.0255 4874 4.1553 0000 2.9810 1.0700 2.1456 1.9409 4312 4.5013 0000 2.7862 1.0957 1.8231 1.8564 3759 4.9379 0000 2.5933 1.1194 1.5006 1,7718 3222 5.4990 0000 2.4034 1.1402 1.1781 1.6872 2709 6.2290 0000 2.2182 1 1562

Explanation / Answer

Here the Regression equation is math achievement y = 13.5351 + 2.6818 *ses -1.3783 *female +0.2622 *int_l-2.8402 * minority

1. From the regression output (Model summary) , the overall F value is 414.54 and the corresponding P-value is less than 0.0005 .

This means the model is signficant.

So there is an association between gender, socio economic status and math achievement after controlling for minority.

From the model1, the the variables ses, female aresignificant as their p values are less than 0.0005.

2. From the output, the R-square value increases due to interaction term, the % of the variation change is 0.02%. This change is not significant as the P-value is 0.1551 which is high.

So the effect of socio-economic on math achievement doesn't vary signficantly across gender.

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